Outcome Prediction in Mild Traumatic Brain Injury: Age and Clinical Variables Are Stronger Predictors than CT Abnormalities

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Abstract
Mild traumatic brain injury (mTBI) is a common heterogeneous neurological disorder with a wide range of possible clinical outcomes. Accurate prediction of outcome is desirable for optimal treatment. This study aimed both to identify the demographic, clinical, and computed tomographic (CT) characteristics associated with unfavorable outcome at 6 months after mTBI, and to design a prediction model for application in daily practice. All consecutive mTBI patients (Glasgow Coma Scale [GCS] score: 13–15) admitted to our hospital who were age 16 or older were included during an 8-year period as part of the prospective Radboud University Brain Injury Cohort Study (RUBICS). Outcome was assessed at 6 months post-trauma using the Glasgow Outcome Scale-Extended (GOSE), dichotomized into unfavorable (GOSE score 1–6) and favorable (GOSE score 7–8) outcome groups. The predictive value of several variables was determined using multivariate binary logistic regression analysis. We included 2784 mTBI patients and found CT abnormalities in 20.7% of the 1999 patients that underwent a head CT. Age, extracranial injuries, and day-of-injury alcohol intoxication proved to be the strongest outcome predictors. The presence of facial fractures and the number of hemorrhagic contusions emerged as CT predictors. Furthermore, we showed that the predictive value of a scheme based on a modified Injury Severity Score (ISS), alcohol intoxication, and age equalled the value of one that also included CT characteristics. In fact, it exceeded one that was based on CT characteristics alone. We conclude that, although valuable for the identification of the individual mTBI patient at risk for deterioration and eventual neurosurgical intervention, CT characteristics are imperfect predictors of outcome after mTBI.